Pattern recognition problem

Image recognition is a typical pattern recognition problem .

图像识别是典型的模式识别问题。

The implementation and test of a pattern recognition problem prove the feasibility of this method .

经过对一个模式识别问题的实现和测试，证明了这种设计方法的可行性。

Intrusion detection is essentially a pattern recognition problem .

入侵检测实质上是模式识别问题。

Automatic emotion recognition of human speech can be viewed as a pattern recognition problem .

语音信号的情感识别也可以看成一个模式识别问题。

Multi-classifiers fusion is a powerful solution to the difficult pattern recognition problem .

多分类器融合是解决复杂模式识别问题的有效办法。

The classification of apple mealiness is a pattern recognition problem in essential .

苹果的粉质化分类本质是一个模式识别问题。

Off-line Handwritten Chinese Characters Recognition ( OHCCR ) is always a complex pattern recognition problem .

脱机手写体汉字识别一直是一个很复杂的模式识别问题。

Face recognition is essentially a typical small - sample pattern recognition problem in sparse hyper-high dimensional space .

人脸识别实质是稀疏超高维空间、典型的小样本模式识别问题。

As the evaluation of slope stability is a pattern recognition problem , the paper established a slope stability evaluation of fuzzy pattern recognition model .

由于评价边坡稳定是一个模式识别问题，因此文中建立了边坡稳定评价的模糊识别模式模型。

In the uncertainty of the system to solve the small sample of the pattern recognition problem , the gray system theory showed a good performance .

灰色系统理论在解决小样本的不确定性问题中的模式辨识问题方面表现出了良好的性能。

Currency recognition is a pattern recognition problem , which includes following three main parts , Data acquisition , Feature extraction and Classifier design .

货币识别是一个模式识别问题，主要包括以下三大部分：数据采集、特征提取和分类器的设计。

Speech emotion recognition can be viewed as a pattern recognition problem , which is built on the basis of feature extraction .

语音情感识别属于模式识别的一种，是建立在特征参数提取的基础上。

Support vector machines theory possesses outstanding advantages in solving small sample learning and prediction , nonlinear and high dimensional pattern recognition problem .

它在解决小样本学习和预测、非线性及高维模式识别问题中具有突出的优势。

Face recognition is the most challenging research detection is a high-dimensional pattern recognition problem in pattern recognition , machine learning and computer vision .

人脸识别是模式识别、机器学习和计算机视觉领域最具挑战性的研究方向之一，是一个高维的模式识别问题。

Simulation results of the circle in the square problem , the function approximation problem and the pattern recognition problem show the effectiveness of the proposed algorithm .

圆的点分类问题、函数逼近问题和模式识别问题这三个数值实验的结果显示了新算法的效果。

We successfully apply it on a simple pattern recognition problem and exhibit the potential of the artificial immune system on the intelligent information retrieval system .

最后展望了将人工免疫系统这一新的机器学习机制应用到智能化信息检索系统中的前景。

Nowadays , just as the other algorithm to solve the pattern recognition problem s , SVMs faces on the problem of parameter selection and optimization .

SVMs发展到现在，同其他解决模式识别问题的方法一样，也遇到了参数选择与参数优化问题，怎样选择与优化对SVMs的推广性能起核心作用的核函数，成为阻碍SVMs进一步发展的难题。

In addition , face recognition is a small sample pattern recognition problem ; subspace classifier constructed on small sample set is biased and unstable .

另外，人脸识别是典型的高维小样本问题，在小的样本集上训练得到的子空间分类器往往是有偏的且分类结果不稳定。

Face gender recognition is to discriminate the gender based on the inputted face image , which is a typical two-class pattern recognition problem .

人脸性别识别是指根据输入的人脸图像判别其性别，它是一个典型的两类模式识别问题。

Traditional computer has fast and efficient logic operations functions , but its poor image thinking ability and no self-learning ability are not fit for solving pattern recognition problem .

传统的冯诺依曼计算机虽然具有快速、高效的逻辑运算等功能，但其形象思维能力差、无自我学习能力等缺点对于形象思维领域的模式识别等问题却是无能为力。

Remote sensing image classification is a typical pattern recognition problem , properties of surface features and classification is the specific application of pattern recognition technology in the field of remote sensing .

遥感影像分类是一种典型的模式识别问题，对遥感影像上的地物属性进行识别和分类，是模式识别技术在遥感领域的具体应用。

Handwritten Chinese character recognition is a very complex pattern recognition problem , many years of research shows that the effect of a single method are limited , various methods have their own advantages and limitations .

手写体汉字识别是一个非常复杂的多模式识别问题，多年研究实践表明，单一方法的效果是有限的，各种方法有其自身的优点和局限性。

The principle of the Intrusion Detection is to get the information of the network traffics and then analyze them to determine whether the system is under attack . So we can look the intrusion detecting as a Pattern Recognition problem .

网络入侵检测问题本质上是获取网络上的数据流量信息并根据一定的方法进行分析，来判断是否受到了攻击或者入侵，因此，入侵检测问题可以理解为模式识别问题。

In practice , there are two key technology problems needed to be solved about the star sensor . The one is star pattern recognition problem , the other is spacecraft attitude determination ( estimation ) problem based on CCD star sensor .

星敏感器在实际的应用中，需要解决两大关键技术问题，其一是星模式的识别问题，其二是基于CCD星敏感器的空间飞行器姿态确定（估计）问题。

Intrusion detection is regarded as a pattern recognition problem in term of statistical learning theory ; i. e. , normal behavior and anomaly are distinguished on the basis of observed datum such as network flows and audit records of host .

在基于统计学习理论的入侵检测研究中，把入侵检测看作是一个模式识别问题，即根据网络流量特征和主机审计记录等观测数据来区分系统的正常行为和异常行为。

In this paper , a sphere neighborhood covering-structuring approach based on neural network for pattern recognition problem of large scale is introduced . And the method has been used for the typical pattern recognition problem of large scale such as Handwritten Chinese Characters recognition .

针对大模式类识别问题，介绍基于神经网络球面领域覆盖构造方法的思想，并给出覆盖构造法在典型大模式类识别问题的应用；

The xiang thinking is a process of information processing . It can be explained with the theory of pattern recognition and problem solving .

象思维的实现过程是一个信息加工的过程，其实现过程可从模式识别理论和问题解决理论得到较好地阐释。

As protein Secondary Structure Prediction is a pattern recognition classification problem , and SVM has many special advantages in solving small sample , nonlinear and high dimensional pattern recognition , so we use this approach for the research .

因为蛋白质二级结构预测实际上是一个模式识别问题，支持向量机方法在解决小样本、非线性及高维模式识别中表现出许多特有的优势，因此本文使用该方法预测二级结构。

Least squares support vector machine ( hereinafter referred to as LS-SVM ) method has advantage in simple structure , global optimal and generalization ability and is applied for pattern recognition , regression problem and other fields .

最小二乘支持向量机（以下简称LS-SVM）具有结构简单、全局最优和推广能力强等优点，被应用于模式识别和回归处理问题等领域。

Star pattern recognition is the key problem of satellite position determination from start sensor .

星图识别是星敏感器确定卫星姿态的关键技术。